George C. Canavos

669 total citations
28 papers, 487 citations indexed

About

George C. Canavos is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, George C. Canavos has authored 28 papers receiving a total of 487 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Statistics and Probability, 5 papers in Statistics, Probability and Uncertainty and 3 papers in Artificial Intelligence. Recurrent topics in George C. Canavos's work include Statistical Distribution Estimation and Applications (11 papers), Advanced Statistical Methods and Models (7 papers) and Statistical Methods and Bayesian Inference (6 papers). George C. Canavos is often cited by papers focused on Statistical Distribution Estimation and Applications (11 papers), Advanced Statistical Methods and Models (7 papers) and Statistical Methods and Bayesian Inference (6 papers). George C. Canavos collaborates with scholars based in United States, Greece and United Kingdom. George C. Canavos's co-authors include Ioannis A. Koutrouvelis, Michael Spinelli, Simos G. Meintanis, Don Miller, Chris P. Tsokos, Kenneth W. Kemp, Heinz Roland Weistroffer, Paul G. Hoel, Charles H. Smith and Donna Miller and has published in prestigious journals such as Journal of the American Statistical Association, Technometrics and Water Resources Research.

In The Last Decade

George C. Canavos

26 papers receiving 453 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
George C. Canavos United States 11 125 91 71 54 52 28 487
Gerald Keller Canada 10 49 0.4× 42 0.5× 23 0.3× 25 0.5× 45 0.9× 15 693
José Garcı́a Pérez Spain 11 97 0.8× 76 0.8× 12 0.2× 109 2.0× 33 0.6× 56 739
William G. Marchal United States 14 85 0.7× 20 0.2× 21 0.3× 14 0.3× 46 0.9× 28 606
William G. Stillwell United States 6 27 0.2× 33 0.4× 18 0.3× 48 0.9× 66 1.3× 9 519
Michael Conklin United States 9 123 1.0× 31 0.3× 43 0.6× 18 0.3× 164 3.2× 57 657
Mary A. Meyer United States 6 29 0.2× 99 1.1× 9 0.1× 31 0.6× 79 1.5× 11 429
Berna Yazıcı Türkiye 9 129 1.0× 68 0.7× 9 0.1× 18 0.3× 78 1.5× 39 608
David A. Seaver United States 6 35 0.3× 37 0.4× 12 0.2× 26 0.5× 61 1.2× 12 462
Giovanni C. Porzio Italy 7 73 0.6× 32 0.4× 9 0.1× 26 0.5× 74 1.4× 21 491
Peter Bruce United States 9 64 0.5× 38 0.4× 10 0.1× 28 0.5× 102 2.0× 14 533

Countries citing papers authored by George C. Canavos

Since Specialization
Citations

This map shows the geographic impact of George C. Canavos's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by George C. Canavos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George C. Canavos more than expected).

Fields of papers citing papers by George C. Canavos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by George C. Canavos. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by George C. Canavos. The network helps show where George C. Canavos may publish in the future.

Co-authorship network of co-authors of George C. Canavos

This figure shows the co-authorship network connecting the top 25 collaborators of George C. Canavos. A scholar is included among the top collaborators of George C. Canavos based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with George C. Canavos. George C. Canavos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Koutrouvelis, Ioannis A., et al.. (2010). Cumulant Plots for Assessing the Gamma Distribution. Communication in Statistics- Theory and Methods. 39(4). 626–641. 4 indexed citations
2.
Canavos, George C. & Ioannis A. Koutrouvelis. (2009). An introduction to the design & analysis of experiments. 9 indexed citations
3.
Koutrouvelis, Ioannis A., et al.. (2006). Testing the Fit of Gamma Distributions Using the Empirical Moment Generating Function. Communication in Statistics- Theory and Methods. 35(3). 527–540. 11 indexed citations
4.
Koutrouvelis, Ioannis A., George C. Canavos, & Simos G. Meintanis. (2004). Estimation in the three-parameter inverse Gaussian distribution. Computational Statistics & Data Analysis. 49(4). 1132–1147. 22 indexed citations
5.
Canavos, George C., et al.. (2004). An analysis of the variation in billing charges of medical providers: causes and implications. Applied Economics. 36(21). 2377–2384.
6.
Weistroffer, Heinz Roland, et al.. (2001). A merit pay allocation model for college faculty based on performance quality and quantity. Economics of Education Review. 20(1). 41–49. 9 indexed citations
7.
Spinelli, Michael & George C. Canavos. (2000). Investigating the Relationhip between Employee Satisfaction and Guest Satisfaction. Cornell Hotel and Restaurant Administration Quarterly. 41(6). 29–33. 78 indexed citations
8.
Koutrouvelis, Ioannis A. & George C. Canavos. (1999). Estimation in the Pearson type 3 distribution. Water Resources Research. 35(9). 2693–2704. 36 indexed citations
9.
Koutrouvelis, Ioannis A. & George C. Canavos. (1997). Estimation in the three-parameter gamma distribution based on the empirical moment generation function. Journal of Statistical Computation and Simulation. 59(1). 47–62. 16 indexed citations
10.
Canavos, George C., et al.. (1995). Modern Business Statistics. The American Statistician. 49(4). 397–397. 6 indexed citations
11.
Canavos, George C.. (1992). Probabilidad y estadística: aplicaciones y métodos. Virtual Defense Library (Ministerio de Defensa). 58 indexed citations
12.
Canavos, George C.. (1988). The sensitivity of the one-sample and two-sample student t statistics. Computational Statistics & Data Analysis. 6(1). 39–46. 10 indexed citations
13.
Canavos, George C. & Charles H. Smith. (1986). Sensitivity of a bayesian inference to prior assumptions. Journal of Statistical Computation and Simulation. 25(1-2). 25–36. 4 indexed citations
14.
Canavos, George C., et al.. (1986). Applied Probability and Statistical Methods.. Journal of the American Statistical Association. 81(393). 258–258. 6 indexed citations
15.
Canavos, George C. & Ioannis A. Koutrouvelis. (1984). The Robustness of Two-Sided Tolerance Limits for Normal Distributions. Journal of Quality Technology. 16(3). 144–149. 15 indexed citations
16.
Canavos, George C.. (1974). On the robustness of a Bayes estimate.
17.
Canavos, George C.. (1974). A Monte Carlo investigation of experimental data requirements for fitting polynomial functions. NASA Technical Reports Server (NASA). 7(4). e34962–e34962. 2 indexed citations
18.
Canavos, George C.. (1973). An Empirical Bayes Approach for the Poisson Life Distribution. IEEE Transactions on Reliability. R-22(2). 91–96. 13 indexed citations
19.
Canavos, George C., et al.. (1973). Bayesian Estimation of Life Parameters in the Weibull Distribution. Operations Research. 21(3). 755–763. 39 indexed citations
20.
Canavos, George C.. (1967). A comparative analysis of two concepts in the generation of uniform pseudo-random numbers. 485–501. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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